Computational approach to modeling microbiome landscapes associated with chronic human disease progression.

A microbial community is a dynamic system undergoing constant change in response to internal and external stimuli. These changes can have significant implications for human health. However, due to the difficulty in obtaining longitudinal samples, the study of the dynamic relationship between the microbiome and human health remains a challenge. Here, we introduce a novel computational strategy that uses massive cross-sectional sample data to model microbiome landscapes associated with chronic disease development. The strategy is based on the rationale that each static sample provides a snapshot of the disease process, and if the number of samples is sufficiently large, the footprints of individual samples populate progression trajectories, which enables us to recover disease progression paths along a microbiome landscape by using computational approaches. To demonstrate the validity of the proposed strategy, we developed a bioinformatics pipeline and applied it to a gut microbiome dataset available from a Crohn's disease study. Our analysis resulted in one of the first working models of microbial progression for Crohn's disease. We performed a series of interrogations to validate the constructed model. Our analysis suggested that the model recapitulated the longitudinal progression of microbial dysbiosis during the known clinical trajectory of Crohn's disease. By overcoming restrictions associated with complex longitudinal sampling, the proposed strategy can provide valuable insights into the role of the microbiome in the pathogenesis of chronic disease and facilitate the shift of the field from descriptive research to mechanistic studies.

A parallel computational framework for ultra-large-scale sequence clustering analysis.

Motivation: The rapid development of sequencing technology has led to an explosive accumulation of genomic data. Clustering is often the first step to be performed in sequence analysis. However, existing methods scale poorly with respect to the unprecedented growth of input data size. As high-performance computing systems are becoming widely accessible, it is highly desired that a clustering method can easily scale to handle large-scale sequence datasets by leveraging the power of parallel computing. Results: In this paper, we introduce SLAD (Separation via Landmark-based Active Divisive clustering), a generic computational framework that can be used to parallelize various de novo operational taxonomic unit (OTU) picking methods and comes with theoretical guarantees on both accuracy and efficiency. The proposed framework was implemented on Apache Spark, which allows for easy and efficient utilization of parallel computing resources. Experiments performed on various datasets demonstrated that SLAD can significantly speed up a number of popular de novo OTU picking methods and meanwhile maintains the same level of accuracy. In particular, the experiment on the Earth Microbiome Project dataset (∼2.2B reads, 437 GB) demonstrated the excellent scalability of the proposed method. Availability and implementation: Open-source software for the proposed method is freely available at https://www.acsu.buffalo.edu/~yijunsun/lab/SLAD.html. Supplementary information: Supplementary data are available at Bioinformatics online.

SENSE: Siamese neural network for sequence embedding and alignment-free comparison.

MOTIVATION: Sequence analysis is arguably a foundation of modern biology. Classic approaches to sequence analysis are based on sequence alignment, which is limited when dealing with large-scale sequence data. A dozen of alignment-free approaches have been developed to provide computationally efficient alternatives to alignment-based approaches. However, existing methods define sequence similarity based on various heuristics and can only provide rough approximations to alignment distances. RESULTS: In this article, we developed a new approach, referred to as SENSE (SiamEse Neural network for Sequence Embedding), for efficient and accurate alignment-free sequence comparison. The basic idea is to use a deep neural network to learn an explicit embedding function based on a small training dataset to project sequences into an embedding space so that the mean square error between alignment distances and pairwise distances defined in the embedding space is minimized. To the best of our knowledge, this is the first attempt to use deep learning for alignment-free sequence analysis. A large-scale experiment was performed that demonstrated that our method significantly outperformed the state-of-the-art alignment-free methods in terms of both efficiency and accuracy. AVAILABILITY AND IMPLEMENTATION: Open-source software for the proposed method is developed and freely available at https://www.acsu.buffalo.edu/∼yijunsun/lab/SENSE.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Clinical and public health implications of periodontal and systemic diseases: An overview.

Severe periodontitis is defined by extensive loss of the tooth attachment apparatus. It is the sixth most common human disease and is estimated to affect 11.2% of the global adult population, hence representing a significant healthcare, social, and economic burden. Since the 1990s, multiple epidemiologic, experimental, and interventional studies have evidenced how periodontitis may also impact systemic health and it has been independently associated with the majority of chronic noncommunicable diseases. The evidence supporting these associations, mainly focusing on diabetes, pregnancy complications, and cardiovascular disease, was thoroughly reviewed in 2012 by an international consensus workshop. In the last 5 years, however, important advances have been made, not only in our understanding of the etiopathogenesis of periodontitis, or concerning the mounting evidence regarding the independent associations between periodontitis, diabetes, and cardiovascular disease, but also with many other systemic diseases including metabolic disease and obesity, rheumatoid arthritis, certain cancers, respiratory diseases, and cognitive disorders including Alzheimer's disease. This review describes these scientific advances by gathering together the existing evidence on the importance and relevance of the associations between periodontitis and many systemic diseases.

Effects of periodontal disease on glycemic control, complications, and incidence of diabetes mellitus.

Diabetes mellitus is a group of metabolic disorders with high mortality and morbidity associated with complications such as cardiovascular disease, kidney disease, and stroke. The prevalence of diabetes is 9.4% in US adults, and prevalence increases markedly with age, with 1 in 4 adults aged ≥65 years affected by diabetes. The estimated number of adults with type 2 diabetes globally almost tripled between 2002 and 2017, reflecting increases seen in the USA and elsewhere. This increase raises concerns about the increased morbidity and mortality associated with the complications of diabetes, including periodontal disease and tooth loss. There is a reciprocal adverse relationship between diabetes and periodontal disease, with diabetes as a major risk factor for periodontal disease, and in those patients with diabetes who also have periodontal disease then there are adverse effects on glycemic control and complications such as cardiovascular disease and end stage renal disease. In this review, those studies detailing the adverse effects of periodontal disease and diabetes will be discussed. Also, evidence is accumulating that periodontitis may play a role in increasing the incidence of new cases of type 2 diabetes, and possibly gestational diabetes. Of course, these studies need to be expanded to better understand the effects of periodontitis on diabetes glycemic control, complications, prediabetes, and the incidence of new cases. However, given the tremendous burden of diabetes on society, the dental profession should be proactive in preventing and treating periodontal disease, not only to preserve the dentition, but also to minimize the adverse effects of periodontitis on diabetes and its complications.

Diabetes as a potential risk for periodontitis: association studies.

Diabetes affects one in 10 adults and periodontal disease affects four in 10 adults in the USA, and they are linked. Individuals with diabetes are more likely to suffer from periodontal disease and periodontal disease affects glycemic control and complications of diabetes. The role of diabetes as a risk factor for periodontal disease and other oral conditions will be discussed in this review. The fact that type 2 diabetes, especially uncontrolled, is a risk factor for periodontal disease has long been recognized. However, the role of type 1 diabetes and gestational diabetes in periodontal risk has recently been described. Also, diabetes as a risk factor for tooth loss has more recently been described and the deleterious effects of tooth loss, especially edentulism, in comparing the diets of patients with diabetes is now fully appreciated. From longitudinal studies it is clear that diabetes often precedes periodontitis and, hence, may contribute to the causal pathway of periodontitis. Other oral manifestations of diabetes include increased risk of oral and nonoral (vaginal) fungal infections. In patients with diabetes there is often reduced salivary flow associated with diabetes medications and neuropathy affecting the salivary glands. This may lead to increased caries. Burning mouth, resulting from diabetes neuropathy, and taste impairment may also be seen. It has long been known that there is delayed wound healing in patients with diabetes, especially if uncontrolled. Hence, it is critical to achieve good glycemic control before carrying out surgical procedures or dental implant placement in patients with diabetes.

Periodontal disease and cancer: Epidemiologic studies and possible mechanisms.

Epidemiologic and cancer control studies on the association of periodontal disease and cancer risk mostly suggest a positive association with overall cancer risk and certain specific types of cancer. These findings are generally consistent among cross-sectional and longitudinal studies. In this paper, we review epidemiologic studies and current knowledge on periodontal disease and cancer, with a focus on those studies conducted in the years following the Joint European Federation of Periodontology/American Academy of Periodontology Workshop on "Periodontitis and Systemic Diseases" in November 2012. This review also explores the role of chronic inflammation as a biologically plausible mechanistic link between periodontal disease and risk of cancer. Furthermore, it highlights studies that have examined the potential importance of certain periodontal pathogens in this association.

Recent epidemiologic trends in periodontitis in the USA.

The most important development in the epidemiology of periodontitis in the USA during the last decade is the result of improvements in survey methodologies and statistical modeling of periodontitis in adults. Most of these advancements have occurred as the direct outcome of work by the joint initiative known as the Periodontal Disease Surveillance Project by the Centers for Disease Control and Prevention and the American Academy of Periodontology that was established in 2006. This report summarizes some of the key findings of this important initiative and its impact on our knowledge of the epidemiology of periodontitis in US adults. This initiative first suggested new periodontitis case definitions for surveillance in 2007 and revised them slightly in 2012. This classification is now regarded as the global standard for periodontitis surveillance and is used worldwide. First, application of such a standard in reporting finally enables results from different researchers in different countries to be meaningfully compared. Second, this initiative tackled the concern that prior national surveys, which used partial-mouth periodontal examination protocols, grossly underestimated the prevalence of periodontitis of potentially more than 50%. Consequently, because previous national surveys significantly underestimated the true prevalence of periodontitis, it is not possible to extrapolate any trend in periodontitis prevalence in the USA over time. Any difference calculated may not represent any actual change in periodontitis prevalence, but rather is a consequence of using different periodontal examination protocols. Finally, the initiative addressed the gap in the need for state and local data on periodontitis prevalence. Through the direct efforts of the Centers for Disease Control and Prevention and the American Academy of Periodontology initiative, full-mouth periodontal probing at six sites around all nonthird molar teeth was included in the 6 years of National Health and Nutrition Examination Surveys from 2009-2014, yielding complete data for 10 683 dentate community-dwelling US adults aged 30 to 79 years. Applying the 2012 periodontitis case definitions to the 2009-2014 National Health and Nutrition Examination Surveys data, the periodontitis prevalence turned out to be much greater than previously estimated, namely affecting 42.2% of the population with 7.8% of people experiencing severe periodontitis. It was also discovered that only the moderate type of periodontitis is driving the increase in periodontitis prevalence with age, not the mild or the severe types whose prevalence do not increase consistently with age, but remain ~ 10%-15% in all age groups of 40 years and older. The greatest risk for having periodontitis of any type was seen in older people, in males, in minority race/ethnic groups, in poorer and less educated groups, and especially in cigarette smokers. The Centers for Disease Control and Prevention and the American Academy of Periodontology initiative reported, for the first time, the periodontitis prevalence estimated at both local and state levels, in addition to the national level. Also, this initiative developed and validated in field studies a set of eight items for self-reported periodontitis for use in direct survey estimates of periodontitis prevalence in existing state-based surveys. These items were also included in the 2009-2014 National Health and Nutrition Examination Surveys for validation against clinically determined cases of periodontitis. Another novel result of this initiative is that, for the first time, the geographic distribution of practicing periodontists in relation to the geographic distribution of people with severe periodontitis is illustrated. In summary, the precise periodontitis prevalence and distribution among subgroups in the dentate US noninstitutionalized population aged 30-79 years is better understood because of application of valid periodontitis case definitions to full-mouth periodontal examination, in combination with reliable information on demographic and health-related measures. We now can monitor the trend of periodontitis prevalence over time as well as guide public health preventive and intervention initiatives for the betterment of the health of the adult US population.

Validation of self-reported measures of periodontitis in a Spanish Population.

BACKGROUND AND OBJECTIVE: Use of self-reported questionnaires in Dentistry may be useful to estimate the prevalence of periodontitis in epidemiological studies. This study aims to assess the accuracy of self-reporting for predicting the prevalence of periodontitis in a Spanish population participating in a diabetes incidence study. MATERIALS AND METHODS: Data were collected from 231 patients participating in the Di@bet.es study. Eight questions about periodontal health were included in a health patient-reported questionnaire. The outcomes from self-reporting were validated against a full-mouth periodontal examination. Multivariable logistic regression predictive modeling was used to determine the sensitivity, specificity, and area under the receiver operator characteristic curve (AUROCC). RESULTS: Self-reported gum health, loose teeth, tooth appearance, and use of dental floss were associated with different definitions of severe periodontitis. Correlations between responses to the questions were weak. The question "Do you think you might have gum disease?" combined with demographic and well-established risk factors resulted in an AUC value of 0.75, sensitivity of 75.2%, and specificity of 60.6% for severe periodontitis. The answer to 4 questions combined with age, educational level, smoking status, and tooth loss was 76.4% sensitive and 63.5% specific, with an AUC of 0.75 in predicting prevalence of ≥25% of teeth with probing pocket depth (PPD) ≥6 mm. CONCLUSION: Predictive models, combining self-reporting on oral health status with demographic and risk factors, were useful for estimating the prevalence of severe periodontitis in the Spanish population.

Composition and diversity of the subgingival microbiome and its relationship with age in postmenopausal women: an epidemiologic investigation.

BACKGROUND: The extent to which the composition and diversity of the oral microbiome varies with age is not clearly understood. METHODS: The 16S rRNA gene of subgingival plaque in 1219 women, aged 53-81 years, was sequenced and its taxonomy annotated against the Human Oral Microbiome Database (v.14.5). Composition of the subgingival microbiome was described in terms of centered log(2)-ratio (CLR) transformed OTU values, relative abundance, and prevalence. Correlations between microbiota abundance and age were evelauted using Pearson Product Moment correlations. P-values were corrected for multiple testing using the Bonferroni method. RESULTS: Of the 267 species identified overall, Veillonella dispar was the most abundant bacteria when described by CLR OTU (mean 8.3) or relative abundance (mean 8.9%); whereas Streptococcus oralis, Veillonella dispar and Veillonella parvula were most prevalent (100%, all) when described as being present at any amount. Linear correlations between age and several CLR OTUs (Pearson r = - 0.18 to 0.18), of which 82 (31%) achieved statistical significance (P < 0.05). The correlations lost significance following Bonferroni correction. Twelve species that differed across age groups (each corrected P < 0.05); 5 (42%) were higher in women ages 50-59 compared to ≥70 (corrected P < 0.05), and 7 (48%) were higher in women 70 years and older. CONCLUSIONS: We identified associations between several bacterial species and age across the age range of postmenopausal women studied. Understanding the functions of these bacteria could identify intervention targets to enhance oral health in later life.

Suppressed hepatic bile acid signalling despite elevated production of primary and secondary bile acids in NAFLD.

OBJECTIVE: Bile acids are regulators of lipid and glucose metabolism, and modulate inflammation in the liver and other tissues. Primary bile acids such as cholic acid and chenodeoxycholic acid (CDCA) are produced in the liver, and converted into secondary bile acids such as deoxycholic acid (DCA) and lithocholic acid by gut microbiota. Here we investigated the possible roles of bile acids in non-alcoholic fatty liver disease (NAFLD) pathogenesis and the impact of the gut microbiome on bile acid signalling in NAFLD. DESIGN: Serum bile acid levels and fibroblast growth factor 19 (FGF19), liver gene expression profiles and gut microbiome compositions were determined in patients with NAFLD, high-fat diet-fed rats and their controls. RESULTS: Serum concentrations of primary and secondary bile acids were increased in patients with NAFLD. In per cent, the farnesoid X receptor (FXR) antagonistic DCA was increased, while the agonistic CDCA was decreased in NAFLD. Increased mRNA expression for cytochrome P450 7A1, Na+-taurocholate cotransporting polypeptide and paraoxonase 1, no change in mRNA expression for small heterodimer partner and bile salt export pump, and reduced serum FGF19 were evidence of impaired FXR and fibroblast growth factor receptor 4 (FGFR4)-mediated signalling in NAFLD. Taurine and glycine metabolising bacteria were increased in the gut of patients with NAFLD, reflecting increased secondary bile acid production. Similar changes in liver gene expression and the gut microbiome were observed in high-fat diet-fed rats. CONCLUSIONS: The serum bile acid profile, the hepatic gene expression pattern and the gut microbiome composition consistently support an elevated bile acid production in NAFLD. The increased proportion of FXR antagonistic bile acid explains, at least in part, the suppression of hepatic FXR-mediated and FGFR4-mediated signalling. Our study suggests that future NAFLD intervention may target the components of FXR signalling, including the bile acid converting gut microbiome.

Gut microbiome may contribute to insulin resistance and systemic inflammation in obese rodents: a meta-analysis.

A number of studies have associated obesity with altered gut microbiota, although results are discordant regarding compositional changes in the gut microbiota of obese animals. Herein we used a meta-analysis to obtain an unbiased evaluation of structural and functional changes of the gut microbiota in diet-induced obese rodents. The raw sequencing data of nine studies generated from high-fat diet (HFD)-induced obese rodent models were processed with QIIME to obtain gut microbiota compositions. Biological functions were predicted and annotated with KEGG pathways with PICRUSt. No significant difference was observed for alpha diversity and Bacteroidetes-to-Firmicutes ratio between obese and lean rodents. Bacteroidia, Clostridia, Bacilli, and Erysipelotrichi were dominant classes, but gut microbiota compositions varied among studies. Meta-analysis of the nine microbiome data sets identified 15 differential taxa and 57 differential pathways between obese and lean rodents. In obese rodents, increased abundance was observed for Dorea, Oscillospira, and Ruminococcus, known for fermenting polysaccharide into short chain fatty acids (SCFAs). Decreased Turicibacter and increased Lactococcus are consistent with elevated inflammation in the obese status. Differential functional pathways of the gut microbiome in obese rodents included enriched pyruvate metabolism, butanoate metabolism, propanoate metabolism, pentose phosphate pathway, fatty acid biosynthesis, and glycerolipid metabolism pathways. These pathways converge in the function of carbohydrate metabolism, SCFA metabolism, and biosynthesis of lipid. HFD-induced obesity results in structural and functional dysbiosis of gut microbiota. The altered gut microbiome may contribute to obesity development by promoting insulin resistance and systemic inflammation.

Chronic kidney disease, uremic milieu, and its effects on gut bacterial microbiota dysbiosis.

Several lines of evidence suggest that gut bacterial microbiota is altered in patients with chronic kidney disease (CKD), though the mechanism of which this dysbiosis takes place is not well understood. Recent studies delineated changes in gut microbiota in both CKD patients and experimental animal models using microarray chips. We present 16S ribosomal RNA gene sequencing of both stool pellets and small bowel contents of C57BL/6J mice that underwent a remnant kidney model and establish that changes in microbiota take place in the early gastrointestinal tract. Increased intestinal urea concentration has been hypothesized as a leading contributor to dysbiotic changes in CKD. We show that urea transporters (UT)-A and UT-B mRNA are both expressed throughout the whole gastrointestinal tract. The noted increase in intestinal urea concentration appears to be independent of UTs' expression. Urea supplementation in drinking water resulted in alteration in bacterial gut microbiota that is quite different than that seen in CKD. This indicates that increased intestinal urea concentration might not fully explain the CKD- associated dysbiosis.

Periodontal health and gingival diseases and conditions on an intact and a reduced periodontium: Consensus report of workgroup 1 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions.

Periodontal health is defined by absence of clinically detectable inflammation. There is a biological level of immune surveillance that is consistent with clinical gingival health and homeostasis. Clinical gingival health may be found in a periodontium that is intact, i.e. without clinical attachment loss or bone loss, and on a reduced periodontium in either a non-periodontitis patient (e.g. in patients with some form of gingival recession or following crown lengthening surgery) or in a patient with a history of periodontitis who is currently periodontally stable. Clinical gingival health can be restored following treatment of gingivitis and periodontitis. However, the treated and stable periodontitis patient with current gingival health remains at increased risk of recurrent periodontitis, and accordingly, must be closely monitored. Two broad categories of gingival diseases include non-dental plaque biofilm-induced gingival diseases and dental plaque-induced gingivitis. Non-dental plaque biofilm-induced gingival diseases include a variety of conditions that are not caused by plaque and usually do not resolve following plaque removal. Such lesions may be manifestations of a systemic condition or may be localized to the oral cavity. Dental plaque-induced gingivitis has a variety of clinical signs and symptoms, and both local predisposing factors and systemic modifying factors can affect its extent, severity, and progression. Dental plaque-induced gingivitis may arise on an intact periodontium or on a reduced periodontium in either a non-periodontitis patient or in a currently stable "periodontitis patient" i.e. successfully treated, in whom clinical inflammation has been eliminated (or substantially reduced). A periodontitis patient with gingival inflammation remains a periodontitis patient (Figure 1), and comprehensive risk assessment and management are imperative to ensure early prevention and/or treatment of recurrent/progressive periodontitis. Precision dental medicine defines a patient-centered approach to care, and therefore, creates differences in the way in which a "case" of gingival health or gingivitis is defined for clinical practice as opposed to epidemiologically in population prevalence surveys. Thus, case definitions of gingival health and gingivitis are presented for both purposes. While gingival health and gingivitis have many clinical features, case definitions are primarily predicated on presence or absence of bleeding on probing. Here we classify gingival health and gingival diseases/conditions, along with a summary table of diagnostic features for defining health and gingivitis in various clinical situations.

Periodontal disease severity and cancer risk in postmenopausal women: the Buffalo OsteoPerio Study.

PURPOSE: Few prospective studies have reported on relationships between objective periodontal disease (PD) measures and cancer risk. This association was examined in 1,337 postmenopausal women participating in the Buffalo OsteoPerio Study. METHODS: Oral alveolar crestal height (ACH) was measured using oral radiographs. Incident cancers were adjudicated with medical records. Hazard ratios (HRs) and 95 % confidence intervals (CIs) for associations between ACH and incident cancer outcomes were estimated using Cox proportional hazards models. RESULTS: There were 203 confirmed total incident cancer cases during follow-up (12.2 ± 4.2 years). After adjusting for age and smoking, there were no statistically significant associations between ACH-defined PD categories and total cancer risk (mild/moderate vs. none: HR 1.33, 95 % CI 0.91-1.94; severe vs. none: HR 1.20, 95 % CI 0.77-1.86). ACH-defined PD categories were not associated with common site-specific cancers. Whole-mouth mean and worst-site ACH (per 1 mm loss) were significantly associated with increased risk of lung (adjusted HR 1.81, 95 % CI 1.30-2.54; adjusted HR 1.34, 95 % CI 1.08-1.66, respectively), but not total or other site-specific cancer. Smoking status modified the associations between continuous ACH variables and total cancer risk; measures of PD were associated with total cancer among smokers but not never smokers (interaction p = 0.02 and p < 0.01 for whole-mouth mean and worst-site ACH, respectively). CONCLUSIONS: ACH-defined PD was associated with total cancer risk in ever but not never smoking postmenopausal women. Whole-mouth mean and worst-site ACH were associated with increased lung cancer risk. However, these results need to be interpreted cautiously given the small number of lung cancer cases (n = 18). Further research utilizing a larger sample is warranted to confirm the relationships among oral bone loss, site-specific cancers, and total cancer.

Periodontitis prevalence in adults ≥ 65 years of age, in the USA.

The older adult population is growing rapidly in the USA and it is expected that by 2040 the number of adults ≥ 65 years of age will have increased by about 50%. With the growth of this subpopulation, oral health status, and periodontal status in particular, becomes important in the quest to maintain an adequate quality of life. Poor oral health can have a major impact, leading to tooth loss, pain and discomfort, and may prevent older adults from chewing food properly, often leading to poor nutrition. Periodontitis is monitored in the USA at the national level as part of the Healthy People 2020 initiative. In this report, we provide estimates of the overall burden of periodontitis among adults ≥ 65 years of age and after stratification according to sociodemographic factors, modifiable risk factors (such as smoking status), the presence of other systemic conditions (such as diabetes) and access to dental care. We also estimated the burden of periodontitis within this age group at the state and local levels. Data from the National Health and Nutrition Examination Survey 2009/2010 and 2011/2012 cycles were analyzed. Periodontal measures from both survey cycles were based on a full-mouth periodontal examination. Nineteen per cent of adults in this subpopulation were edentulous. The mean age was 73 years, 7% were current smokers, 8% lived below the 100% Federal Poverty Level and < 40% had seen a dentist in the past year. Almost two-thirds (62.3%) had one or more sites with ≥ 5 mm of clinical attachment loss and almost half had at least one site with probing pocket depth of ≥ 4 mm. We estimated the lowest prevalence of periodontitis in Utah (62.3%) and New Hampshire (62.6%) and the highest in New Mexico, Hawaii, and the District of Columbia each with a prevalence of higher than 70%. Overall, periodontitis is highly prevalent in this subpopulation, with two-thirds of dentate older adults affected at any geographic level. These findings provide an opportunity to determine how the overall health-care management of older adults should consider the improvement of their oral health conditions. Many older adults do not have dental insurance and are also likely to have some chronic conditions, which can adversely affect their oral health.

History of periodontal disease diagnosis and lung cancer incidence in the Women's Health Initiative Observational Study.

PURPOSE: While some evidence suggests that periodontal disease (PD) might be positively associated with lung cancer, prospective studies in women are limited. Previous findings may reflect residual confounding by smoking. The study aims to determine whether history of PD diagnosis is associated with incident lung cancer in a large cohort of postmenopausal women. METHODS: Prospective analyses were conducted in a cohort of 77,485 postmenopausal women enrolled in the Women's Health Initiative Observational Study. History of PD (prevalence of 26.1 %) was self-reported, and 754 incident lung cancer cases occurred during an average 6.8 (SD ± 2.6) years of follow-up. Cox proportional hazards regression analysis was used to estimate hazard ratios (HRs) and 95 % confidence intervals (CIs). RESULTS: Overall, PD was positively associated with lung cancer risk after adjusting for detailed smoking history including smoking status and pack-years of smoking (HR 1.24, 95 % CI 1.07-1.45). There was a positive additive interaction between PD with pack-years of smoking (p = 0.02), suggesting a potential synergistic effect between PD and smoking intensity on lung cancer. The association between PD and lung cancer was stronger in former smokers. When restricted to never-smokers, PD was not associated with lung cancer (HR 1.02, 95 % CI 0.68-1.53). CONCLUSIONS: Periodontal disease was not independently associated with lung cancer in non-smoking postmenopausal women. However, smoking and PD jointly increased lung cancer risk beyond that expected from the sum of the each effect separately. The potential synergism between PD and smoking on lung cancer warrants further examination.

Common risk factors in the management of periodontal and associated systemic diseases: the dental setting and interprofessional collaboration.

UNLABELLED: There is a role for dentistry in the interprofessional management of chronic diseases by addressing common risk factors BACKGROUND: A critical scientific foundation has developed for management of risk factors common to major diseases including periodontal disease, caries, diabetes, heart disease, and cancer. PURPOSE: The purpose of this paper is to critically review this scientific literature. This will provide the basis for the current and future role of the dental setting in common risk factor identification and modification; with an emphasis on the role of the dental hygienist. METHODS: A systematic review of the literature and analysis of the relevant papers was undertaken to support the recommendations. CONCLUSIONS: We propose that the appropriate risk factor management procedures be adopted in the dental setting for smoking cessation, reduction of sugar consumption, and weight control in those patients at risk for one or a combination of the following diseases: periodontal disease, caries, diabetes, heart disease and certain cancers.

Risk factors for periodontal disease.

Risk factors play an important role in an individual's response to periodontal infection. Identification of these risk factors helps to target patients for prevention and treatment, with modification of risk factors critical to the control of periodontal disease. Shifts in our understanding of periodontal disease prevalence, and advances in scientific methodology and statistical analysis in the last few decades, have allowed identification of several major systemic risk factors for periodontal disease. The first change in our thinking was the understanding that periodontal disease is not universal, but that severe forms are found only in a portion of the adult population who show abnormal susceptibility. Analysis of risk factors and the ability to statistically adjust and stratify populations to eliminate the effects of confounding factors have allowed identification of independent risk factors. These independent but modifiable, risk factors for periodontal disease include lifestyle factors, such as smoking and alcohol consumption. They also include diseases and unhealthy conditions such as diabetes mellitus, obesity, metabolic syndrome, osteoporosis, and low dietary calcium and vitamin D. These risk factors are modifiable and their management is a major component of the contemporary care of many periodontal patients. Genetic factors also play a role in periodontal disease and allow one to target individuals for prevention and early detection. The role of genetic factors in aggressive periodontitis is clear. However, although genetic factors (i.e., specific genes) are strongly suspected to have an association with chronic adult periodontitis, there is as yet no clear evidence for this in the general population. It is important to pursue efforts to identify genetic factors associated with chronic periodontitis because such factors have potential in identifying patients who have a high susceptibility for development of this disease. Many of the systemic risk factors for periodontal disease, such as smoking, diabetes and obesity, and osteoporosis in postmenopausal women, are relatively common and can be expected to affect most patients with periodontal disease seen in clinics and dental practices. Hence, risk factor identification and management has become a key component of care for periodontal patients.

Effect of periodontal disease on diabetes: systematic review of epidemiologic observational evidence.

BACKGROUND: Periodontal disease and diabetes mellitus are common, chronic diseases worldwide. Epidemiologic and biologic evidence suggest periodontal disease may affect diabetes. OBJECTIVE: To systematically review non-experimental, epidemiologic evidence for effects of periodontal disease on diabetes control, complications and incidence. DATA SOURCES: Electronic bibliographic databases, supplemented by hand searches of recent and future issues of relevant journals. STUDY ELIGIBILITY CRITERIA AND PARTICIPANTS: Longitudinal and cross-sectional epidemiologic, non-interventional studies that permit determination of directionality of observed effects were included. STUDY APPRAISAL AND SYNTHESIS METHODS: Four reviewers evaluated pair-wise each study. Review findings regarding study results and quality were summarized in tables by topic, using the PRISMA Statement for reporting and the Newcastle-Ottawa System for quality assessment, respectively. From 2246 citations identified and available abstracts screened, 114 full-text reports were assessed and 17 included in the review. RESULTS: A small body of evidence supports significant, adverse effects of periodontal disease on glycaemic control, diabetes complications, and development of type 2 (and possibly gestational) diabetes. LIMITATIONS: There were only a limited number of eligible studies, several of which included small sample sizes. Exposure and outcome parameters varied, and the generalizability of their results was limited. CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS: Current evidence suggests that periodontal disease adversely affects diabetes outcomes, and that further longitudinal studies are warranted.